Canadian researchers have created a computer model that performs tasks like a human brain. It also sometimes forgets things.

There are times when I wonder why so many scientists are spending so much time trying to recreate something as fickle and full of fogginess as the human brain.

But who am I kidding? Those dyspeptic moments inevitably pass, as anyone who’s been following this blog knows. Every few months, it seems, I’m back writing about the latest attempt to build machines that can learn to recognize objects or even develop cognitive skills.

And now there’s Spaun.

Staying on task

Its full name is the Semantic Pointer Architecture Unified Network, but Spaun sounds way more epic. It’s the latest version of a techno brain, the creation of a Canadian research team at the University of Waterloo.

So what makes Spaun different from a mindboggingly smart artificial brain like IBM’s Watson? Put simply, Watson is designed to work like a supremely powerful search engine, digging through an enormous amount of data at breakneck speed and using complex algorithms to derive an answer. It doesn’t really care about how the process works; it’s mainly about mastering information retrieval.

But Spaun tries to actually mimic the human brain’s behavior and does so by performing a series of tasks, all different from each other. It’s a computer model that can not only recognize numbers with its virtual eye and remember them, but also can manipulate a robotic arm to write them down.

Spaun’s “brain” is divided into two parts, loosely based on our cerebral cortex and basal ganglia and its simulated 2.5 million neurons–our brains have 100 billion–are designed to mimic how researchers think those two parts of the brain interact.

Say, for instance, that its “eye” sees a series of numbers. The artificial neurons take that visual data and route it into the cortex where Spaun uses it to perform a number of different tasks, such as counting, copying the figures, or solving number puzzles.

Ask it a question and it doesn’t answer immediately. No, it pauses slightly, about as long as a human might. And if you give Spaun a long list of numbers to remember, it has an easier time recalling the ones it received first and last, but struggles a bit to remember the ones in the middle.

“There are some fairly subtle details of human behavior that the model does capture,” says Chris Eliasmith, Spaun’s chief inventor. “It’s definitely not on the same scale. But it gives a flavor of a lot of different things brains can do.”

Brain drains

The fact that Spaun can move from one task to another brings us one step closer to being able to understand how our brains are able to shift so effortlessly from reading a note to memorizing a phone number to telling our hand to open a door.

And that could help scientists equip robots with the ability to be more flexible thinkers, to adjust on the fly. Also, because Spaun operates more like a human brain, researchers could use it to run health experiments that they couldn’t do on humans.

Recently, for instance, Eliasmith ran a test in which he killed off the neurons in a brain model at the same rate that neurons die in people as they age. He wanted to see how the loss of neurons affected the model’s performance on an intelligence test.

One thing Eliasmith hasn’t been able to do is to get Spaun to recognize if it’s doing a good or a bad job. He’s working on it.

Gathering intelligence

Here are a few other recent developments in brain research and artificial intelligence:

I can’t get this song out of your head: Scientists in Berlin wired guitarists playing a duet with electrodes and found that when they had to closely coordinate their playing, their brain activity became synchronized. But when they weren’t coordinated, when one was leading and the other following, their brain activity was distinctly different.

One day the brain may actually understand itself: A team of MIT neuroscientists has developed a way to monitor how brain cells coordinate with each other to control specific behaviors, such as telling the body to move. Not only could this help them map brain circuits to see how tasks are carried out, but it also may provide insight into how psychiatric diseases develop.

Deep thinking is so yesterday: The top prize in a recent competition sponsored by pharmaceutical giant Merck went to a team of researchers from the University of Toronto who used a form of artificial intelligence known as deep learning to help discover molecules that could become new drugs.

So robots will learn how to stare at smart phones?: To teach robots how to function in social situations, scientists at Carnegie-Mellon University are tracking groups of people with head-mounted cameras to see when and where their eyes converge in social settings.

Unfortunately, they keep trying to hide nuts: By using the deceptive behavior of birds and squirrels as a model, researchers at Georgia Tech have been able to develop robots that can trick each other.